AIMC Topic: Exons

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Improved prediction of smoking status via isoform-aware RNA-seq deep learning models.

PLoS computational biology
Most predictive models based on gene expression data do not leverage information related to gene splicing, despite the fact that splicing is a fundamental feature of eukaryotic gene expression. Cigarette smoking is an important environmental risk fac...

A deep learning approach to identify gene targets of a therapeutic for human splicing disorders.

Nature communications
Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to mutation lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of splicing modulator compound...

MET Exon 14 Skipping: A Case Study for the Detection of Genetic Variants in Cancer Driver Genes by Deep Learning.

International journal of molecular sciences
BACKGROUND: Disruption of alternative splicing (AS) is frequently observed in cancer and might represent an important signature for tumor progression and therapy. Exon skipping (ES) represents one of the most frequent AS events, and in non-small cell...

CADD-Splice-improving genome-wide variant effect prediction using deep learning-derived splice scores.

Genome medicine
BACKGROUND: Splicing of genomic exons into mRNAs is a critical prerequisite for the accurate synthesis of human proteins. Genetic variants impacting splicing underlie a substantial proportion of genetic disease, but are challenging to identify beyond...

Machine learning based CRISPR gRNA design for therapeutic exon skipping.

PLoS computational biology
Restoring gene function by the induced skipping of deleterious exons has been shown to be effective for treating genetic disorders. However, many of the clinically successful therapies for exon skipping are transient oligonucleotide-based treatments ...

A network-based computational framework to predict and differentiate functions for gene isoforms using exon-level expression data.

Methods (San Diego, Calif.)
MOTIVATION: Alternative splicing makes significant contributions to functional diversity of transcripts and proteins. Many alternatively spliced gene isoforms have been shown to perform specific biological functions under different contexts. In addit...

Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

PLoS computational biology
Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause of neurodevelopmental disability. Whole transcriptome sequencing (RNA-Seq) offer insights into mechanisms underlying FASD, but gene-level analysis pro...

Deep-learning augmented RNA-seq analysis of transcript splicing.

Nature methods
A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its reliance on high sequencing coverage. We report DARTS (https://github.com/Xinglab/DARTS), a computational framework that integrates deep-learning-based predictions...

Discerning novel splice junctions derived from RNA-seq alignment: a deep learning approach.

BMC genomics
BACKGROUND: Exon splicing is a regulated cellular process in the transcription of protein-coding genes. Technological advancements and cost reductions in RNA sequencing have made quantitative and qualitative assessments of the transcriptome both poss...

Identification of 170 New Long Noncoding RNAs in .

BioMed research international
Long noncoding RNAs (lncRNAs) are transcripts generally longer than 200 nucleotides with no or poor protein coding potential, and most of their functions are also poorly characterized. Recently, an increasing number of studies have shown that lncRNAs...